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Delivery · Version 1.3.0 · Reviewed 2026-08-02

Pull Request Risk Classifier

Make a defensible decision about pull request risk tiering and review requirement selection with evidence, explicit trade-offs, and a verification plan.

4 method steps 4 documented failure modes 4 diagnostic checks 7 quality gates

Classifies change risk from blast radius, reversibility, state, security, compatibility, and validation evidence. It grounds the decision in changed behavior, dependency reach, data effects, permissions, rollout controls, test evidence, and rollback constraints and explicitly prevents using lines changed or file labels as the risk score while a tiny irreversible contract change ranks low.

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What this skill helps you do

  • Pull request risk tiering
  • Review requirement selection
  • Release guardrail assignment

How Pull Request Risk Classifier works

You provide

Change scope, traffic volume, and current release process

It inspects

Exposure control and abort signal quality for pull request risk tiering

It decides

A review requirement selection plan staged by blast radius

You verify

Rollback rehearsed against the deployed schema and data

What it checks first

Pull Request Risk Classifier classifies change risk from blast radius, reversibility, state, security, compatibility, and validation evidence. It grounds the decision in changed behavior, dependency reach, data effects, permissions, rollout controls, test evidence, and rollback constraints and explicitly prevents using lines changed or file labels as the risk score while a tiny irreversible contract change ranks low. Use it when the work involves Pull request risk tiering, Review requirement selection, Release guardrail assignment.

  1. Whether exposure can be changed without a redeploy, which decides how fast a bad release can be stopped.
  2. The promotion signal and whether it can detect harm the error rate cannot see.
  3. Whether rollback remains available after the first irreversible step in the release.
  4. Batch size, since large releases make attribution and rollback disproportionately harder.

Failure modes it recognizes

  • A canary promoted on infrastructure metrics while a business metric silently degrades.
  • A release coupled to a schema change, so rollback stops being possible after the first write.
  • Session affinity sending the same users to the canary, biasing the comparison.
  • A promotion gate on a metric that updates more slowly than the damage accumulates.

Answers it will reject

  • Treating deploy and release as the same event, which removes control over exposure.
  • Promoting because no alert fired, which confuses absence of detection with absence of harm.
  • Shipping a large batch to reduce release overhead, which raises the cost of every failure.

Decision rules it applies

  • Separate deploy from release with a flag so exposure is reversible without a redeploy.
  • Fix the abort criteria and thresholds before the rollout begins.
  • Sequence schema changes so the previous version keeps working throughout.

Evidence it asks for

  • Compare canary and control on a business metric with enough traffic to be meaningful.
  • Rehearse rollback against the deployed schema, not the previous one.
  • Automate abort so promotion does not depend on a human watching.

The method inside

  1. Establish what is actually true about pull request risk tiering from the supplied evidence, and mark what is missing.
  2. Identify the mechanism behind review requirement selection rather than restating the symptom.
  3. Choose the smallest defensible change for release guardrail assignment, weighing impact, confidence, effort, and reversibility.
  4. Record consequences, rollback, and open questions

Deliverables

  • Pull request risk tiering assessment
  • Review requirement selection decision and action plan
  • Release guardrail assignment verification checklist

Evidence requirements

  • Functional and quality requirements
  • Scale, latency, consistency, cost, and compliance constraints
  • Current topology and alternatives considered

Quality gates

  • Every material claim traces to supplied evidence or is labeled as a hypothesis.
  • The response follows the declared deliverable contract.
  • No execution, access, measurement, or verification is invented.
  • Secrets and personal data are redacted rather than repeated.
  • The user receives a concrete independent verification step.
  • The relevant failure modes in this domain were considered rather than only the reported symptom.
  • No listed anti-pattern was recommended as a solution.

Example task

Input

Apply the pull request risk classifier to our current pull request risk tiering work. We need a concrete decision, bounded changes, and evidence that the result is correct.

Expected output

Start with changed behavior, dependency reach, data effects, permissions, rollout controls, test evidence, and rollback constraints. The highest-risk failure is using lines changed or file labels as the risk score while a tiny irreversible contract change ranks low. Let the highest credible impact and weakest recovery path set the floor, then adjust confidence from evidence. Verify the result by backtesting classifications against incidents, reverts, and expert labels across a representative change sample.

Boundaries and compatibility

Ideal for

  • Pull request risk tiering: produce a decision or artifact grounded in supplied evidence.
  • Review requirement selection: produce a decision or artifact grounded in supplied evidence.
  • Release guardrail assignment: produce a decision or artifact grounded in supplied evidence.

Out of scope

  • Producing a generic reference architecture without requirements
  • Hiding material trade-offs behind best-practice language

Agent compatibility

  • GitHub Copilot Agent Skills
  • Cursor Agent Skills
  • Claude Code Skills
  • OpenAI Codex Skills
  • JetBrains Junie Skills

Tool policy: Advisory by default. No tools are assumed. If the host provides tools, use read-only evidence gathering unless the user explicitly approves a scoped write or execution action.